Coal workers' pneumoconiosis (CWP), or “black lung,” is a major health problem resulting from prolonged exposure to respirable coal dusts (dusts with mass mean diameters typically less than 10 μm). To reduce this problem and provide protection against the occurrence of CWP, current coal mining regulations require that personnel exposure to respirable coal mine dusts be limited to an eight hour time weighted average that does not exceed 2.0 mg/m3.30 C.F.R. § 70.100 (1995).
The standard measurement technique for this determination is continuous sampling of the mine atmosphere through a small, 10 mm cyclone at a nominal flow rate of 2.01 pm. While this is the generally accepted standard technique for determining respirable dust concentrations, such determinations are cumbersome and time-consuming to complete. As a result, alternative approaches to the measurement of respirable dust concentrations are being studied for their adequacy and accuracy.
In addition, many mines use diesel engines extensively, and the use of diesel engines makes the measurement more complex for a number of reasons. First, the particles deposited on a filter of a conventional measuring device are due both to diesel particulate matter (DPM) and respirable dust, and there is no simple technique to determine their relative contributions to the total mass deposited. Second, since there are significant and different adverse health effects related to DPM (DPM is a suspected carcinogen), the maximum allowable time weighted average concentration for DPM is a factor of 10 lower than that for respirable dust.
Consequently, it is helpful not only to be able to determine the airborne mass concentrations of both DPM and respirable dust, but DPM concentrations need to be measured at significantly lower concentrations. For DPM, the current standard is NIOSH 5040, which is based upon the determination of elemental carbon and organic carbon. NIOSH Manual of Analytic Methods, 4th ed., DHHS (NIOSH) Publication 94–113, Edited by M. E. Cassinelli and P. F. O'Connor (August 1994). However, the chemical composition of DPM may contain significant components of volatile organic compounds, as great as 55 to 60%, so that under some conditions of diesel operation, these standard determinations may not be valid.
Various techniques have been proposed and studied to address these measurement problems. One technique involves the measurement of the pressure drop across a filter onto which particles are deposited by applying of D'Arcy's Law for flow through a porous bed of particles, where the pressure drop across the particle bed, or layer, is a function of the particle concentration and size. See, Volkwein, J. C., Schoeneman, and Page, S. J., Laboratory Evaluation of Pressure Differential Based Respirable Dust Detector Tube, Appl. Occ. & Enviro. Hyg., Vol. 15, No. 1, pp. 158–164 (2000).
While this technique appears to work reasonably well for samples that contain no DPM, the presence of even minute quantities of DPM renders the technique unreliable. Even for pure respirable dust samples, significant variations in the pressure drop per unit mass, due most probably to differing particle size distributions, can occur, often resulting in meaningless or skewed measurements.
Another technique involves aerodynamic separation of DPM and respirable dusts. This approach has shown that, typically, particles with diameters less than about 0.7 μm are the products of diesel combustion while larger particles are due to respirable dusts, although in the region of particle diameters between 0.7 μm and 1.0 μm, overlap between the two sources of particles often occurs which makes the determination of individual mass concentrations difficult. In addition, even simple aerodynamic separation techniques require not only very precise flow control but also result in additional filter mass measurements that are even more cumbersome and time-consuming to complete.
Continuous, real-time mass measurements using devices, such as a Tapered Element Oscillating Microbalance (TEOM), have also been proposed for monitoring either DPM or respirable dusts. However, such devices are incapable of discriminating between the two when both exist simultaneously. In addition, while the extension of these continuous, real-time measurement techniques to individual personnel monitoring is feasible, the cost of such devices becomes a major concern.
The use of light scattering as a technique for measuring aerosol and/or respirable dust concentrations is known. Light scattering is attractive as a measurement technique because it is simple and generally inexpensive to implement. Currently, there exist several instruments that are available commercially that utilize this technique, although significant differences exist among the various instruments. Some utilize angular intensities measured at a forward angle of around 12°, while some measure the intensity in the angular range of 16° to 18°. Another known light-scattering instrument measures the intensity over the angular range of 45° to 90° with a maximum sensitivity at around 60°.
Most light-scattering devices use a light source with a wavelength of about 900 nm. However, some of these devices become very sensitive to particle size distributions, or average particle diameters, while some become sensitive to the chemical composition of the scattering particles. These effects can introduce unacceptable errors in the determination of mass concentration. In addition, a major criticism of light scattering is that it is not a direct mass measurement. Rather, mass concentrations are inferred based upon some method of calibration, yet because of particle size, chemical composition, or some other effect, the calibration may not be sufficient to yield accurate determinations of mass concentration over a broad range of aerosol or respirable dust characteristics.
Thus, it would be desirable to determine the combinations of scattering angle and light-source wavelength where the effects of particle size and chemical composition are either negligible or minimal, so as to enable accurate measurements of mass concentrations of particulates, such as respirable dusts, with a light-scattering device.
A related problem encountered in mining environments is that conventional fire sensors that detect the smoke and gases produced during the early stages of developing fires are often compromised by the presence of DPM (as well as background levels of other aerosols or gases) that mimic the signatures of developing fires, often resulting in frequent false, or nuisance, sensor alarms. When the frequency of false alarms is high, the tendency is to either ignore sensors, or to de-energize the sensors, with the potentially catastrophic consequence that an actual fire is not detected.
A commonly used type of smoke detector utilizes light scattering (discussed above) as a technique for detection of developing fires. Currently, there exist many such commercially available detectors that utilize this technique, generally referred as light-scattering smoke detectors or photo-electric smoke detectors. Significant differences exist among the various detectors, for example, angle(s) for detection and light source wavelength.
Another type of smoke detector is an ionization-type smoke detector, which has been used routinely as an early-warning fire sensor since the mid 1970's. Typically, an ionization-type detector comprises an ionization chamber in which there is disposed a source of ions, such as a very low-level radioactive source of Americium 241 (Am 241). Am 241 decays via the emission of alpha particles (He atoms), and as these particles traverse the air space between two field electrodes, both positive and negative ions are created. The positive ions drift to the negative electrode while the negative ions drift to the positive electrode. This separation of ions, coupled with the geometry of the chamber, creates a space charge that distorts the electric field and electric potential within the ion chamber. A third, sensing electrode typically is located between the positive and negative electrodes at a position where the electric potential reaches its maximum distortion.
When smoke enters the air space between the electrodes, the positive and negative ions rapidly attach to the smoke particles, depleting the ion concentrations, which in turn reduce the distortion of the electric potential, causing the potential at the sensing electrode to increase. This change in electric potential provides a measurable indication of the presence of smoke.
While both light-scattering smoke detectors and ionization-type smoke detectors are widely recognized as a useful and inexpensive means in detecting airborne smoke indicative of a fire, the presence of background aerosols and gases, typical in mining and industrial environments, interferes with the ability of conventional detectors to accurately detect smoke.
A significant level of research is being done to address this problem. For smoke, efforts continue to more accurately and completely define the properties of smoke produced from different sources, and to develop improved techniques for smoke measurement. For example, efforts have been made to characterize the signatures of interfering sources using multi-sensor arrays coupled with neural networks, or other multi-signature alarm algorithms.
However, the use of these multi-sensor approaches are generally application-specific in that different applications may require different sensors, and the necessary algorithms can vary significantly from one application to the next. In some of these approaches, it is not only the relative signals from different sensors, but also the manner in which these signals vary with time, that allow for discrimination between smoke and interfering background particulates. In underground mine applications, the use of multi-sensor packages and software to process the signals and make decisions increases the complexity and cost of the system, and necessitates increased system maintenance and sensor replacement.
Therefore, it would be desirable if conventional light-scattering and ionization-type detectors could be configured to discriminate between aerosols produced from fires and common, interfering aerosols and/or gases, such as DPM or any of various other sub-micrometer particles.